Personal navigation systems have received attention from both the industrial and academic research communities in recent years. Numerous target applications have been proposed, including localization for members of a team of firefighters, first responders, and soldiers. In these applications, the safety and efficiency of the entire team depends on the availability of accurate position and orientation (pose) estimates of each team member. While the team is operating within the coverage area of GPS satellites, each person's pose can be reliably estimated. However, a far more challenging scenario occurs when the team is inside a building, in an urban canyon, or under a forest canopy. In these cases, GPS-based global localization is not sufficiently accurate or may be completely unavailable, and pose estimation must be accomplished through secondary means. One popular approach is to equip each person with a body-mounted strap-down Inertial Measurement Unit (IMU) typically comprising three accelerometers and three gyroscopes in orthogonal triads, which measure the person's motion. To mitigate the drift errors in strap-down inertial navigation, conventional systems typically include aiding sensors, such as a camera or laser scanner which sense the color, texture, or geometry of the environment. Each person's pose can then be estimated individually by fusing the available sensing information.